Energy Optimization Model Research Articles

06/01215 Energy optimisation model for a CCHP system with available gas turbines: Kong, X. Q. et al. Applied Thermal Engineering, 2005, 25, (2–3), 377–391

This paper presents the achievements gained in solid sorption refrigeration prototypes since the end of the l970s, when interest in sorption systems was renewed. The applications included are ice making and air conditioning. The latter includes not only cooling and heating, but also dehumidification by desiccant systems. The prototypes presented were designed to use waste heat or solar energy as the main heat source. The waste heat could be from diesel engines or from power plants, in combined cooling, heating and power systems (CCHP). The current technology of adsorption solar-powered icemakers allows a daily ice production of between 4 and 7 kg m−2 of solar collector, with a solar coefficient of performance (COP) between 0.10 and 0.16. The silica gel–water chillers studied can be powered by hot water warmer than 55 °C. The COP is usually around 0.2–0.6, and in some commercially produced machines, it can be up to 0.7. The utilization of such chillers in CCHP systems, hospitals, buildings and grain depots are discussed. Despite their advantages, solid sorption systems still present some drawbacks such as low specific cooling power (SCP) and COP. Thus, some techniques to overcome these problems are also contemplated, together with the perspectives for their broad commercialisation. Among these techniques, a special attention was devoted to innovative adsorbent materials, to advanced cycles and to heat pipes, which are suitable devices not only to improve the heat transfer but also can help to avoid corrosion in the adsorbers. Recent experiments performed by the research group of the authors with machines that employ composite adsorbent material and heat pipes showed that it is possible to achieve a SCP of 770 W kg−1 of salt and COP of 0.39 at evaporation temperatures of −20 °C and generation temperature of 115 °C.

Optimization Model for Energy Planning with CO2 Emission Considerations

This paper considers the problem of reducing CO2 emissions from a power grid consisting of a variety of power-generating plants: coal, natural gas, nuclear, hydroelectric, and alternative energy. The problem is formulated as a mixed integer linear program (MILP) and implemented in GAMS (General Algebraic Modeling System). Preprocessing and variable elimination strategies are used to reduce the size of the model. The model is applied to an existing Ontario Power Generation (OPG) fleet analyzed under three different operating modes: (1) economic mode, (2) environmental mode, and (3) integrated mode. The integrated mode combines the objectives of both the economic and environmental modes through the use of an external pollution index as a conversion factor from pollution to cost. Two carbon dioxide mitigation options are considered in this study: fuel balancing and fuel switching. In addition, four planning scenarios are studied: (1) a base-load demand, (2) a 0.1% growth rate in demand, (3) a 0.5% growth rate in demand, and (4) a 1.0% growth rate in demand. A sensitivity analysis study is carried out to investigate the effect of parameter uncertainties such as uncertainties in natural gas price, coal price, and retrofit costs on the optimal solution. The optimization results show that fuel balancing can contribute to the reduction of the amount of CO2 emissions by up to 3%. Beyond 3% reductions, more stringent measures that include fuel switching and plant retrofitting have to be employed. The sensitivity analysis results indicate that fluctuations in gas price and retrofit costs can lead to similar fuel-switching considerations. The optimal carbon dioxide mitigation decisions are found, however, to be highly sensitive to coal price.

Energy optimization model for a CCHP system with available gas turbines

This paper deals with the problem of optimal energy management of cogeneration system for combined cooling, heating and power production (CCHP). The energy system consists of a gas turbine, an absorption chiller and a heat recovery boiler. A simple linear programming model is presented to determine the optimal strategies that minimize the overall cost of energy for the CCHP system. It is shown that the optimal operation of this system is dependent upon load conditions to be satisfied. In view of energy cost, it is shown that sometimes it may not be optimal to operate the turbine. This is the case when the electric-to-gas cost ratio is very low.

Optimization of solar district heating systems: seasonal storage, heat pumps, and cogeneration

The dynamic energy, emission, and cost optimization model deeco is further developed and applied to the analysis of solar district heating systems with seasonal storage in a pilot project of the Bavarian Research Foundation. The optimum integration of condensing boilers, compression and absorption heat pumps, and cogeneration of heat and power is computed for 100 well insulated housing units with an annual total heat demand of 616 MWh. Collector areas between 1 and 2.5 m 2 per MWh heat demand and water storage volumes between 1.2 and 4.2 m 3 per m 2 collector area satisfy between 32 and 95 per cent of the total heat demand by solar thermal heat. Compared with a reference case with individual condensing boilers and electricity taken from the public grid, selected scenarios achieve (non-renewable primary) energy savings between 15 and 35% associated with cost increases between −20% and 140%; cogeneration turns out to be quite attractive from an economical point of view. With cogeneration and a solar contribution to the heat supply of 80%, emission reductions of CO 2-equivalents by 33%, SO 2 by 20%, and NO x by 22% can be achieved at cost increases of 120%. Fossil fuel savings of more than 40% are possible if electricity is produced from non-fossil energy sources.

ERIS: A model prototype with endogenous technological change

This paper describes the ERIS Model Prototype, developed within the EU-TEEM project as a flexible tool to study different modelling approaches on the endogenisation of technological change in energy optimisation models. The basic formulation and several variants are presented. Some illustrative results and insights obtained with the prototype are discussed and some perspectives for its future development outlined.

Model-based decision support in energy planning

Models have become standard tools in energy planning. Fast computers and ever improving optimisation packages now allow us to solve problems within a few minutes that were out of range 20 years ago and that 10 years ago could only be solved in several CPU–hours. Fully interactive data bank systems with standardised user interfaces and on–line data access support easy modifications and adaptations of energy models, retrieval and display of results, as well as coupling decision support tools to all kinds of data available in the system. This article gives a brief overview of the objectives in energy planning, especially with respect to different planning horizons. It reviews the types of models applied to different applications and the requirements such tools have to satisfy. The second part surveys some applications of energy optimisation models. These examples have been chosen to illustrate different application areas of energy models from short–term optimal power supply up to very long–term (100 years) resource allocation and technology choice, and from optimising a municipal district heat system up to an energy model for the whole world.

Fuzzy data compression for energy optimization models

Calculating energy savings and emission–reduction potentials for municipal energy systems requires computer models with high spatial and temporal disaggregation. Consequently, the computational effort necessary to run such models is considerable. For the optimization models ecco, ecco-solar and deeco, this problem has so far been solved by assuming that the time intervals considered are independent of each other and may, therefore, be optimized consecutively. For minimization of primary energy inputs and emission of pollutants, this approach is sufficient. Optimization of monetary costs and placing of intertemporal emission limits, however, is not possible. Based on fuzzy-set theory, we develop a method with which the up to 8760 input-data sets of the model can be compressed by 1–2 orders of magnitude such that the remaining ones may then be optimized simultaneously. Test runs with original and compressed data sets show good agreement, thus proving the functioning of the method.

Control models for hydroelectric energy optimization

The optimization of hydroelectric energy is addressed via a new multilevel control model, which is used to derive estimates of system firm energy with or without dependable capacity commitments. The model is able to optimize individual turbine operation as well as overall system operation on an hourly and daily basis. The mechanism by which the various models are linked and exchange information ensures full compatibility among the control levels and guarantees operational consistency across all timescales. The model is applied to the Lanier‐Allatoona‐Carters system, located in the southeastern United States, and is suitable for planning as well as operational applications.

Competition and synergy between energy technologies in municipal energy systems

The dynamic energy optimization model deeco is a tool for analyzing competition and synergy between different technologies of the rational use of energy and for utilizing renewable energies. For given time series of the fluctuating heat and electricity demand, deeco calculates the optimal combination of energy-conversion technologies while taking into account local parameters like ambient temperature and insolation. Thus, the model provides a flexible instrument which may support investment decisions when building or restructing municipal energy systems. As an example, deeco was applied to a model city called Würzburg which is based on a real city of the same name located in southern Germany. Gas-fired, medium-size cogeneration units are found to be the best solution (30% primary energy and 2% cost savings) in a cost-benefit comparison with a system providing heat from conventional oil-fired boilers and receiving electricity from the inter-regional public grid. The influence of energy taxes on relative costs of different technologies is analyzed.

97/02468 Energy planning and optimization model for rural development—a case of sustainable agriculture

97/02468 Energy planning and optimization model for rural development—a case of sustainable agriculture

IKARUS - A fundamental concept for national GHG-mitigation strategies

Within the frame of the German IKARUS project a bottom-up energy optimization model and a macroeconomic simulation model based on the input-output approach have been developed. Under the restriction to reduce energy related CO 2 emissions by 25 % until 2005, first model runs have been done for the German Previous States.

95/06390 Integrated energy optimization model for a cogeneration based energy supply system in the process industry

This chapter presents the 582 MWe lignite-based Kemper County Integrated Gasification Combined Cycle (IGCC) power plant, as a case study of the first commercial application of the air-blown Transport Integrated Gasification (TRIG) technology. The Kemper County IGCC plant is a lignite-fueled 2-on-1 IGCC facility incorporating the air-blown TRIG technology jointly developed by the Southern Company; KBR; and the US Department of Energy (DOE) at the Power Systems Development Facility (PSDF) in Wilsonville, Alabama. The plant is owned by the Mississippi Power Company (MPC) and has a calculated nameplate capacity of 830 MWe with a peak net output of 582 MWe. The plant is designed to capture 65% of the entering carbon, which will be sold for enhanced oil recovery (EOR), making the Kemper County plant’s carbon emissions comparable to those of a natural-gas-fired combined cycle power plant.The technical description of the Kemper County Energy Facility will discuss the various technologies used in the plant. Construction activities are essentially complete and commissioning/startup activities are currently underway. Commercial operation is scheduled to begin in the second half of 2016.

Integrated energy optimization model for a cogeneration based energy supply system in the process industry

Most of the continuous process industries generate electricity by cogeneration using the heat energy required for the process. Electricity is also purchased from external sources such as the grid and generated by internal sources such as diesel gensets. This leads to the decision problem of determining the economically optimum energy-mix during short and long term periods. Also it is important to evaluate the various technologies that can improve the energy supply system. This paper presents a mixed integer (0–1) linear programming model to tackle the above decision problem and presents a case study on the application of the model. It is shown that the model provides the methods for determining the optimal strategies that minimize the overall cost of energy for the process industry.

Design and Management of Energy Databases

The planning of energy supply systems is getting more and more complex and involves increasing amounts of data. In the past, these data have been stored on the computer in simple text files, which were accessible via text editors. At present, powerful database management systems (DBMS) provide mature tools for handling data. However, these instruments are not yet widely used in the energy sector. Therefore, sample solutions for two standard problems of energy plannmg are presented, namely, the management of time series and of technology data. In addition, the database structure of the energy-optimization model ecco is discussed in detail.

Optimization model of recrystallization hot rolling of titanium-vanadium steels

An optimization model was built based on the data of a pilot-scale (4.5 MN load, 225 KW power capacity) rolling mill to minimize the austenite grain sizes of Ti−V steels, which prevail at the instant of completion of the static recrystallization during hot rolling. A computer program developed for this optimization model was run for the rolling schedule, which is designed according to the complete recrystallization case. An energy optimization model developed previously was applied to different rolling schedules. The grain size optimization results demonstrate the effectiveness of these modelling approaches in terms of final grain size, final plate thickness, measured and computed roll force and torque values for both the design of the thermomechanical schedules which produce plate with fine-grained microstructures, high strength, and notch toughness and the temperature-reduction schedules of conventional controlled rolling.

Thermodynamic limits to energy optimization

Second-law analysis is used to develop an energy optimization model based on the maximum reuse of exergy contained in the heat flows which emanate from industrial processes. In general, the optimization problem is non-linear. It can be made accessible to linear programming if one considers the energy losses due to smaller-than-unity conversion efficiencies as irrecoverable. Primary energy input is the objective function to be minimized by use of the simplex algorithm. Heat exchangers, heat pumps and cogeneration of electricity and heat are the energy-conservation technologies taken into account. The ideal energy-conservation potentials of industrial systems turn out to be strongly dependent on the shape of the energy-demand profiles. These profiles show the amount of energy (in enthalpy units) demanded at the various exergy (≅ temperature) levels. The Japanese profile, with a steadily decreasing demand from higher to lower exergy levels, results in the biggest savings (up to 60%). West Germany with its peak demand of high temperature heat has only a primary energy savings potential of less than 50%, whereas the Netherlands with a high demand of low-temperature heat may save nearly as much as Japan. Sensitivity analysis, in which we vary the parameters that describe enthalpy and exergy losses during energy-service performance and transportation, shows that under real-world conditions, the possible savings of primary energy may decrease by 10 to 30 percentage points. The model can be used to handle cost restrictions and perform cost optimization with the same mathematics. Thus, it may be used as a tool for designing economically-efficient strategies of resource conservation and pollution abatement.

Soft energy sources in regional energy systems: The case of the Cyclades

We evaluate the potential penetration of renewable energy sources in the region of the Cyclades, which is a complex of Greek islands in the Aegean Sea. The Cyclades area has a significant endogenous potential of wind, solar and geothermal energy. Future energy demand is forecast for two paths. RESOM, a linear programming regional energy optimization model, has been adapted to represent the regional energy system. The results of four scenario runs provide insight on the impact of renewable energy sources.

4393040 In-vitro diagnostic method for detection of acetylsalicylic acid ingestion : Alberto Lopapa, Theodore Hall assigned to Lopapa Institute Inc

In real-time systems, time is usually so critical that other parameters such as energy consumption are often not even considered. However, optimizing the worst energy consumption case can be a key factor in systems with severe power-supply limitations. In this paper we study several memory architectures using combined time and energy optimization models for real-time multitasking systems. Each task is modeled using Lock-MS, a method to optimize the WCET of a task, with an added set of constraints to model in the same way the WCEC (worst case energy consumption). Our tested hardware components focus on instruction fetching, including a lockable cache, a line buffer and a sequential prefetch buffer. We test a variety of instruction fetch alternatives optimizing time and energy consumption. Our results show that the accuracy of the estimation of the number of context switches in the worst case may affect very much the resulting WCEC (up to 8 times in our experiments) and that optimizing the WCEC may provide similar execution times than optimizing the WCET, with up to 5 times less energy consumption Additionally optimization functions combining WCET and WCEC with different weights show very interesting WCET-WCEC trade-offs. This confirms that methodologies testing such optimizations at design time could be very helpful to provide a precise system set-up.

Functional Response and Fitness in a Generalist Filter Feeder, Daphnia Magna (Cladocera: Crustacea)

The functional response of an organism is often assumed to maximize its fitness. We examined the relationship between functional response and body growth, survivorship, and reproduction in Daphnia magna under controlled and comparable conditions. In a previous study we determined that D. magna exhibits a Holling Type II functional response with an asymptotic increase in ingestion rate with increasing food concentration to a maximum rate at an incipient limiting concentration of °104 Chlamydomonas reinhardi cells/cm3 (measured as carbon, 0.2 mg/L) and that observed feeding activity does not follow the predictions of energy optimization models. In this study, we determined the fitness response for cohorts of D. magna (n = 20—30) at 0, 103, 104, 105 and 106 Chlamydomonas reinhardi cells/cm3 using life table methods. Most parameters indicative of fitness (e.g., body growth, fecundity, survivorship, r, and R0) were maximal at 105 cells/cm3 (2.0 mg/L). The optimum food concentration for growth and reproduction remained at 105 cells/cm3 when cohort life spans were truncated in a simulation of mass mortality due to predation or environmental deterioration. The fitness optimum occurred above the incipient limiting concentration and below the maximum food concentration encountered in nature. These appear to be "suboptimal" behavioral and reproductive responses. However, reproductive models of parthenogenesis and resting egg formation along with these feeding, growth, and reproductive responses suggest that Daphnia track the environment in that they are adapted for rapid population increase and for recovery from mass mortality in cyclical environments in conditions for optimal growth that can be expected to reoccur but are of highly variable duration.

Xenopus laevis larvae (Amphibia, Anura) as model suspension feeders

Larvae of the South African clawed frog, Xenopus laevis (Daudin), are efficient, obligate suspension feeders. We examine the relationship between the ambient particle concentration offered these larvae as food and their filtering, ingestion, and buccal pumping rates. We demonstrate that: (i) the larvae can sense and respond to a broad range of particle concentrations, down to 0.2 mg 1−1 (dry weight); (ii) their metabolic needs theoretically can be met by particle concentrations as low as 5 mg 1−1; and (iii) their patterns of regulation of filtering and ingestion fit predictions from certain models used to describe zooplankton feeding dynamics. Two such models are discussed: the modified Monod (Michaelis-Menten) model, with a lower threshold below which the tadpoles do not feed, and an energy optimization model. Both the models and the observed behavior of the tadpoles allow for stability of populations of food organisms. Tadpole feeding dynamics apparently are compatible with both the predictions and assumptions of these models, suggesting similar regulation of feeding by tadpoles and zooplankton. However, the size, morphology, and behavior of X. laevis larvae make their feeding regulation uniquely accessible to direct observation.